A gronomy J our n al • Volume 110 , I ssue 1 • 2 018 1 T he goal of an N recommendation system is to accurately estimate the gap between the N provided by the soil and the N required by the plant. Accurately estimating this gap depends on the ability of the recommendation system to accurately estimate fi eld or subfi eld specifi c economically optimal nitrogen rates (EONR). Current recommendation systems are not as accurate as needed to provide consistently reliable estimates of N needs across years at the fi eld or subfi eld scale. Uncontrollable factors like temperature, rainfall timing, intensity and amount, and interactions of temperature and rainfall with factors such as N source, timing and placement, plant genetics, and soil characteristics combine to make N rate recommendations for an individual fi eld or rates for subfi elds a process guided as much by science as by the best professional judgement of farmers and farm advisors.Substantial evidence has accumulated that EONRs can vary widely across fi elds, within fi elds and over years in the same fi eld for a wide range of crops and geographies. Examples ABSTRACTNitrogen fi xation by the Haber-Bosch process has more than doubled the amount of fi xed N on Earth, signifi cantly infl uencing the global N cycle. Much of this fi xed N is made into N fertilizer that is used to produce nearly half of the world's food. Too much of the N fertilizer pollutes air and water when it is lost from agroecosystems through volatilization, denitrifi cation, leaching, and runoff . Most of the N fertilizer used in the United States is applied to corn (Zea mays L.), and the profi tability and environmental footprint of corn production is directly tied to N fertilizer applications. Accurately predicting the amount of N needed by corn, however, has proven to be challenging because of the eff ects of rainfall, temperature, and interactions with soil properties on the N cycle. For this reason, improving N recommendations is critical for profi table corn production and for reducing N losses to the environment. Th e objectives of this paper were to review current methods for estimating N needs of corn by: (i) reviewing fundamental background information about how N recommendations are created; (ii) evaluating the performance, strengths, and limitations of systems and tools used for making N fertilizer recommendations; (iii) discussing how adaptive management principles and methods can improve recommendations; and (iv) providing a framework for improving N fertilizer rate recommendations.

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A gronomy J our n al • Volume 101, I s sue 2 • 2 0 0 9 269 ABSTRACT Marked spatial and temporal variability in yield response to N fertilizer observed in individual yield response trials creates a high degree of uncertainty when estimating economic optimum rates (EORs) of N for a group of trials and when extrapolating these rates from one location to another. A survey was conducted to characterize and classify variability in yield response to N on subfi eld and fi eld scales. Fertilizer N was applied at fi ve rates (56, 84, 112, 140, and 168 kg N ha -1 ) in many (6-12) replicated strips within three 18-to 24-ha no-till fi elds during two corn (Zea mays L.) growing seasons. Yield responses or yield diff erences between two adjacent strips were measured in 22 to 25 grid cells ha -1 within each fi eld. Cumulative probability distributions (CPDs) were used to estimate the probability that a given N rate produces a yield response less or equal to a specifi ed quantity. Th e yield responses were classifi ed into potential categories with diff erent N fertilizer requirements using apparent soil electrical conductivity (EC a ), digital soil map units, and relative elevation. Analysis indicated that the classifi cations explained <3% variability in yield response to N applied in the near-optimal range, where probabilities of receiving positive and negative marginal returns were the same. Presenting probabilities of yield response observed at diff erent ranges of N fertilization may provide the basis for assessing the uncertainty associated with the variable eff ects of weather and variable supply of N when assessing economic risk and benefi ts of N fertilization in large-scale on-farm studies. P.M. Kyveryga, On-Farm Network, Iowa Soybean Association, 4554 114th Street, Urbandale, IA 50322; A.M. Blackmer, in memory, Dep. of.

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